5 Winning Data-Driven Marketing Strategies
What Is Data-Driven Marketing?
Technology Ushers in the Age of Personalized Marketing
- Identify the demographics of the campaign’s target audience, such as women ages 18 to 34 who spend more than $50 a month on beauty products.
- Determine the products and services that generate the most revenue in that target category.
- Use data analytics tools to gain insight into the campaign’s target audience, and convert those insights into personalized experiences for those customers.
- Apply A/B testing and other variations to learn which message and medium delivers the highest level of customer engagement.
Techniques That Enhance the Customer Experience
- Unified customer data platforms combine customer data from online and offline sources to extract insights that shape the customer experience.
- Artificial intelligence-based proactive analytics provide data collection and analysis functions that convert information about customers, marketing programs, and other business processes into actionable intelligence.
- Contextual interactions apply real-time insights to identify where customers are on their journey, such as browsing product reviews or visiting a brick-and-mortar store, and to coax them into taking the next steps toward the company’s desired outcome.
Customer Value Analytics
- Historical value measures the value of a customer over time and compares it with other periods and other customers for the same periods.
- Current value analyzes a customer’s activity in a shorter time period to compare recent activity with past values to determine the impact of marketing campaigns, new offers, and changed prices.
- Lifetime value applies the analytics over a longer period by multiplying a customer’s average order by purchase frequency to show how the customer’s value has changed over time.
- Cost to serve compares the profit a customer generates to the cost of serving the customer’s support requirements to identify “service drain” customers: customers who buy few or low-margin products but require high sales administration and delivery expenses.
Omnichannel Marketing Strategies
- Identify the channels that customers are using most frequently, and increase their presence on those channels.
- Make sure that the marketing message is consistent across channels in terms of presence, communication, customer experience, and processes used.
- Customize the message at the most opportune moment. Personalization enhances engagement and brand loyalty.
- Measure the impact of marketing activities across channels, and continually optimize processes and messages to improve results.
Other Ways to Improve Customer Engagement
- Decision engineering inverts the traditional marketing model by identifying decision opportunities first, and then running the data analysis. This allows marketers to focus on goals rather than on the analysis itself.
- Advanced analytics applies smart algorithms and other innovative analytics techniques to segment customers based on their specific lifestyles rather than on demographics. This improves the accuracy and effectiveness of customer profiles.
- Cutting-edge technology includes machine learning and other AI technologies, such as chatbots, that engage customers and manage their interaction with the brand. Chatbots have become successful because they’re convenient for marketers and widely accepted by customers.
5 Data-Driven Marketing Strategies
Personalize the Customer Experience
Coordinate Marketing Across Channels
- Establish the data sources, which may include television, radio, mobile apps and alerts, social media, paid search, influencer campaigns, traditional press, videos, podcasts, and other media. Also consider how the target audience will use each source in relation to the campaign’s goals.
- Establish modeling and attribution, so marketers can confirm that data is properly categorized and displayed. Good decisions by marketers about campaigns and customer expectations rely on high-quality data that’s available when and where it’s needed.
- Continually improve the quality of the data by applying data checks and validation to confirm the accuracy and reliability of the information. Continual checks are required because data is constantly being updated and combined in innovative ways.
Use Predictive Analytics to Create an Ideal Customer Profile<
- Predictive analytics identifies behavior patterns in the data a company has collected about customers and potential customers. The patterns are transformed into intelligence that determines which customers are high quality (likely to be converted to sales) and low quality (unlikely to lead to sales).
- Quality data powers the analytics engine and models. The data must be timely, relevant, accurate, and available when and where it’s needed. Inaccurate and obsolete data will skew the model and reduce its usefulness.
- The expertise of team members must be converted into a form that can be imported into the machine-learning model. The interface that connects staff with the analytics engine must provide real-time access to the results of the analyses, so the model can be continually refined.
Apply Big Data to Track Marketing ROI
- Break down departmental silos to promote the free flow of data throughout the organization. In addition, companies must ensure that the data is easy to integrate with other systems and share with internal and external sources, such as sharing social media demographics with affiliate marketers and internal search engine optimization (SEO) teams.
- Ensure that data streams are updated in real-time to promote fast action based on timely and accurate information. Include data “trails” in the stream to allow marketers to compare past performance of campaigns with current campaigns. Streaming analytics helps marketers identify new business models, product enhancements, and revenue sources.
- Apply visualization tools that simplify complex data and communicate the results of analytics in a way that’s easier for nonmathematicians to grasp. Visualization also helps data scientists and marketers discuss the results of the analyses and their implications for future campaigns.
- Conduct smart business experiments based on variations of marketing approaches to gain insight and discover alternatives. Even simple business experiments can provide keys to rapid revenue growth opportunities.
- Base marketing decisions on past customer data by using data-based tools to assign values to unknowns, forecast the potential for obstacles, and determine the best ways to avoid and mitigate risks.
Transfer Offline Data to Online Environments via Data Onboarding
What Do Marketers Use to Analyze Big Data?
- It has a fast, scalable, and intuitive interface that facilitates data-driven decision-making.
- It smoothly integrates with analytics platforms, tag managers, content management systems, and third-party data.
- It performs multipage, A/B, and split URL testing of sites, mobile apps, and mobile sites.
- Its audience targeting options include data export, preview mode, campaign schedule, stats engine, and behavioral targeting.
Google Analytics, Google PageSpeed Insights, and Google Search Console
Adobe Creative Cloud
- It gives businesses a choice of four purchase plans.
- It’s an affordable option for photographers.
- New features are available immediately.
- Its cloud-based storage and collaboration tools boost productivity.
- It provides companies with “seamless consistency across disciplines.”
- Monitor brand reputations by discovering all mentions on the internet and triggering alerts whenever a new mention appears.
- Create content that’s optimized for search engines and designed to attract an audience for your marketing for many months or years.
- Find the most frequently shared content related to whichever topic you search for. Results can be filtered by date, content type, language, word count, and country.
- Calculate content marketing ROI by measuring the level of engagement for every piece of published content, and average engagement by network, content type, or other category.
- View the most shared backlinks to a campaign’s content sorted by total engagements, domain links, or external links.
- SEO Toolkit is used for keyword research, competitive analysis, page optimization, and link building.
- Advertising Toolkit helps identify optimal keywords for paid advertising that balance traffic building with affordability.
- Social Media Toolkit manages the company’s social media feeds by scheduling and tracking posts.
- Content Marketing Toolkit analyzes the posts in a marketing campaign and suggests ways to optimize the content to improve its search ranking.
- Competitive Research Toolkit lets marketers reverse engineer their competitors’ online operations to identify backlinks, traffic, and organic research.
- E-commerce integration with a range of web services, including WordPress and Shopify
- Support for targeted audience campaigns, including automated follow-ups
- Personalized order notifications
- An extension for the Google Chrome browser
- Demographic information is pulled automatically from URLs and contact records as soon as they’re added.
- Users can send emails and make voice calls to contacts (in conjunction with Sales Hub), and log and save call information inside contact records.
- Users can merge multiple contact lists from other sources.
- Users can publish email blasts directly from Facebook, Instagram, and other social media.
- Users can test multiple versions of an email marketing campaign.
Data-Driven Marketing Benefits
Improve Media Buying, Customer Targeting
- Reach lapsed customers by offering them deals on the company’s top-selling products.
- Identify seasonal buyers, and predict when they’ll be most receptive to special offers on their favorite categories of products.
- Persuade offline customers to become online customers by offering personalized recommendations and online-only promotions.
- Enhance engagement with the company’s brands by promoting exclusive offers for loyal customers, providing high-value customers with incentives to join loyalty programs.
- Upsell on a previous purchase by offering discounts on matching accessories or other complementary products.
- Cross-sell based on the customer’s previous purchase via promotions on products in a similar category, such as tablets for laptop purchasers.
- Keep customers informed of new products, targeting frequent buyers of similar products.
- Promote upgrades to purchased products when updates become available.
Continually Update the Marketing Message
- Make sure your site matches your message. Products and marketing strategies often change faster than elements on the company’s website. For example, the most important attributes of featured products should match the message in the company’s “what we do” description.
- Keep your message consistent. When the message is updated in one medium, the change must be represented in related information on all other platforms.
- Update auxiliary marketing material. For example, companies often have a standard pitch deck that introduces customers to the company and its products. Each time the market message is updated, rework the pitch deck and other marketing resources to match the change.
- Make sure staff members are informed of the new message. Prepare a presentation on the update that internal teams, new hires, and partners can view.
- Emphasize how the product meets customers’ needs today. Products evolve to meet the changing needs of customers. Data-driven marketing helps companies stay in tune with the problems their customers face so they can explain how the product solves their problems.
How to Use Data-Driven Insights
Techniques for Enhancing Customer Retention
- Stand for something. Consumers establish long-term relationships with brands that share their values. Data-driven marketing helps companies communicate their values to customers.
- Share the company’s momentum. When a company develops a new product or enhances an existing one, it creates internal momentum that propels the business forward. Share the momentum with customers via the company’s marketing message.
- Educate customers about how to use the product. Make training part of the marketing effort by offering in-product onboarding, lifecycle emails, online training, and access to product experts.
- Reciprocate unexpectedly. Offering consistently good service is one of the greatest drivers of repurchases and recommendations. The marketing strategy should use data to be proactive in reaching out to customers to check in or simply to say thank you.
- Treat loyal customers like royalty. People appreciate a company’s efforts to make them feel special. Data-driven marketing extracts information about a company’s high-value customers that can be used to demonstrate how much the company appreciates their loyalty.
Using Machine Learning and AI to Automate Marketing Operations
- Employ dynamic pricing strategies allow businesses to offer flexible prices on products based on customer demand, market trends, and other conditions. Machine learning makes relevant, up-to-date data available to make dynamic pricing more effective.
- Use chatbots to offer 24/7 support that can be personalized based on what the system has learned from its internal and external customer data sources. Machine learning also helps personalize a customer’s shopping experience, such as the recommendations made by Amazon and Netflix.
- Gain lifetime customers by leveraging the insights into customer behavior and preferences that machine learning extracts from the company’s data assets. The more a company knows about its customers, the more accurately it can anticipate their future needs and behaviors.